Literature DB >> 30260320

Online classification of imagined speech using functional near-infrared spectroscopy signals.

Alborz Rezazadeh Sereshkeh1, Rozhin Yousefi, Andrew T Wong, Tom Chau.   

Abstract

OBJECTIVE: Most brain-computer interfaces (BCIs) based on functional near-infrared spectroscopy (fNIRS) require that users perform mental tasks such as motor imagery, mental arithmetic, or music imagery to convey a message or to answer simple yes or no questions. These cognitive tasks usually have no direct association with the communicative intent, which makes them difficult for users to perform. APPROACH: In this paper, a 3-class intuitive BCI is presented which enables users to directly answer yes or no questions by covertly rehearsing the word 'yes' or 'no' for 15 s. The BCI also admits an equivalent duration of unconstrained rest which constitutes the third discernable task. Twelve participants each completed one offline block and six online blocks over the course of two sessions. The mean value of the change in oxygenated hemoglobin concentration during a trial was calculated for each channel and used to train a regularized linear discriminant analysis (RLDA) classifier. MAIN
RESULTS: By the final online block, nine out of 12 participants were performing above chance (p  <  0.001 using the binomial cumulative distribution), with a 3-class accuracy of 83.8%  ±  9.4%. Even when considering all participants, the average online 3-class accuracy over the last three blocks was 64.1 %  ±  20.6%, with only three participants scoring below chance (p  <  0.001). For most participants, channels in the left temporal and temporoparietal cortex provided the most discriminative information. SIGNIFICANCE: To our knowledge, this is the first report of an online 3-class imagined speech BCI. Our findings suggest that imagined speech can be used as a reliable activation task for selected users for development of more intuitive BCIs for communication.

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Mesh:

Year:  2018        PMID: 30260320     DOI: 10.1088/1741-2552/aae4b9

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  9 in total

1.  Brain-Based Binary Communication Using Spatiotemporal Features of fNIRS Responses.

Authors:  Laurien Nagels-Coune; Amaia Benitez-Andonegui; Niels Reuter; Michael Lührs; Rainer Goebel; Peter De Weerd; Lars Riecke; Bettina Sorger
Journal:  Front Hum Neurosci       Date:  2020-04-15       Impact factor: 3.169

2.  Decoding of Walking Imagery and Idle State Using Sparse Representation Based on fNIRS.

Authors:  Hongquan Li; Anmin Gong; Lei Zhao; Wei Zhang; Fawang Wang; Yunfa Fu
Journal:  Comput Intell Neurosci       Date:  2021-02-22

3.  See, Hear, or Feel - to Speak: A Versatile Multiple-Choice Functional Near-Infrared Spectroscopy-Brain-Computer Interface Feasible With Visual, Auditory, or Tactile Instructions.

Authors:  Laurien Nagels-Coune; Lars Riecke; Amaia Benitez-Andonegui; Simona Klinkhammer; Rainer Goebel; Peter De Weerd; Michael Lührs; Bettina Sorger
Journal:  Front Hum Neurosci       Date:  2021-11-25       Impact factor: 3.169

Review 4.  A State-of-the-Art Review of EEG-Based Imagined Speech Decoding.

Authors:  Diego Lopez-Bernal; David Balderas; Pedro Ponce; Arturo Molina
Journal:  Front Hum Neurosci       Date:  2022-04-26       Impact factor: 3.473

5.  Dataset of Speech Production in intracranial.Electroencephalography.

Authors:  Maxime Verwoert; Maarten C Ottenhoff; Sophocles Goulis; Albert J Colon; Louis Wagner; Simon Tousseyn; Johannes P van Dijk; Pieter L Kubben; Christian Herff
Journal:  Sci Data       Date:  2022-07-22       Impact factor: 8.501

6.  A pediatric near-infrared spectroscopy brain-computer interface based on the detection of emotional valence.

Authors:  Erica D Floreani; Silvia Orlandi; Tom Chau
Journal:  Front Hum Neurosci       Date:  2022-09-23       Impact factor: 3.473

7.  An Augmented-Reality fNIRS-Based Brain-Computer Interface: A Proof-of-Concept Study.

Authors:  Amaia Benitez-Andonegui; Rodion Burden; Richard Benning; Rico Möckel; Michael Lührs; Bettina Sorger
Journal:  Front Neurosci       Date:  2020-04-28       Impact factor: 4.677

8.  Performance Improvement of Near-Infrared Spectroscopy-Based Brain-Computer Interface Using Regularized Linear Discriminant Analysis Ensemble Classifier Based on Bootstrap Aggregating.

Authors:  Jaeyoung Shin; Chang-Hwan Im
Journal:  Front Neurosci       Date:  2020-03-04       Impact factor: 4.677

9.  Brain-Computer Interfaces for Children With Complex Communication Needs and Limited Mobility: A Systematic Review.

Authors:  Silvia Orlandi; Sarah C House; Petra Karlsson; Rami Saab; Tom Chau
Journal:  Front Hum Neurosci       Date:  2021-07-14       Impact factor: 3.169

  9 in total

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